code: def plot_approach(power, n):
      """Plot the results on a brain."""
      title = "DICS power map, approach %d" % n
      brain = power_approach1.plot(
          "sample",
          subjects_dir=subjects_dir,
          hemi="both",
          size=600,
          time_label=title,
          title=title,
      )
      # Indicate the true locations of the source activity on the plot.
      brain.add_foci(
          vertices[0][0], coords_as_verts=True, hemi="lh", color="b"
      )
      brain.add_foci(
          vertices[1][0], coords_as_verts=True, hemi="rh", color="b"
      )
      # Rotate the view and add a title.
      brain.show_view(
          azimuth=0, elevation=0, distance=550, focalpoint=(0, 0, 0)
      )
      return brain
  
file_path: mne-python/tutorials/simulation/80_dics.py
imports: import numpy
  from matplotlib import pyplot
  from scipy.signal import coherence, unit_impulse, welch
  import mne
  from mne.beamformer import apply_dics_csd, make_dics
  from mne.datasets import sample
  from mne.minimum_norm import apply_inverse, make_inverse_operator
  from mne.simulation import add_noise, simulate_raw
  from mne.time_frequency import csd_morlet
label_desc: Use image node_id 2 for calling a global function with example usage: plot_approach(power, n) and returns: brain